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alternate case: multivariate normal distribution
Bernstein–von Mises theorem
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posterior distribution converges in total variation distance to a multivariate normal distribution centered at the maximum likelihood estimator θ ^ n {\displaystyleMary Ellen Bock (329 words) [view diff] case mismatch in snippet view article find links to article
dissertation on Certain Minimax Estimators of the Mean of a Multivariate Normal Distribution. As chair of statistics at Purdue from 1995 to 2010, Bock ledGHK algorithm (2,266 words) [view diff] exact match in snippet view article find links to article
distributed independently one can simulate draws from a truncated multivariate normal distribution using draws from a univariate random normal. For example, ifBioctonion (474 words) [view diff] case mismatch in snippet view article find links to article
the American Physical Society D.G. Kabe (1984) "Hypercomplex Multivariate Normal Distribution", Metrika 31(2):63−76 MR744966 A.A. Eliovich & V.I. SanyukStein's unbiased risk estimate (944 words) [view diff] case mismatch in snippet view article find links to article
Charles M. (November 1981). "Estimation of the Mean of a Multivariate Normal Distribution". The Annals of Statistics. 9 (6): 1135–1151. doi:10.1214/aos/1176345632Q-function (2,964 words) [view diff] exact match in snippet view article find links to article
{X} \sim {\mathcal {N}}(\mathbf {0} ,\,\Sigma )} follows the multivariate normal distribution with covariance Σ {\displaystyle \Sigma } and the thresholdJean-François Richard (603 words) [view diff] case mismatch in snippet view article find links to article
Analysis, 1974, 419–452. A Note on the Information Matrix of the Multivariate Normal Distribution, Journal of Econometrics, 3, 1975, 57–60 Bayesian AnalysisLinear belief function (3,955 words) [view diff] exact match in snippet view article find links to article
multiple normal variables with mean μ and covariance Σ. Then, the multivariate normal distribution can be equivalently represented as a moment matrix: M ( X )Minimax estimator (1,961 words) [view diff] exact match in snippet view article find links to article
1094–1116 Stein, C. (1981). "Estimation of the mean of a multivariate normal distribution". Annals of Statistics. 9 (6): 1135–1151. doi:10.1214/aos/1176345632EM algorithm and GMM model (1,230 words) [view diff] exact match in snippet view article find links to article
2019). "Machine Learning —Expectation-Maximization Algorithm (EM)". Medium. Tong, Y. L. (2 July 2020). "Multivariate normal distribution". Wikipedia.Financial correlation (4,165 words) [view diff] exact match in snippet view article find links to article
elliptical. However, only few financial distributions such as the multivariate normal distribution and the multivariate student-t distribution are special casesThurstonian model (1,454 words) [view diff] exact match in snippet view article find links to article
and ri, sample zi. The zij must be sampled from a truncated multivariate normal distribution to preserve their rank ordering. Hajivassiliou's TruncatedSparse PCA (2,317 words) [view diff] exact match in snippet view article find links to article
specifies that data X {\displaystyle X} are generated from a multivariate normal distribution with mean 0 and covariance equal to an identity matrix, andMetropolis–Hastings algorithm (4,556 words) [view diff] exact match in snippet view article find links to article
sufficiently regular Bayesian posteriors as they often follow a multivariate normal distribution as can be established using the Bernstein–von Mises theoremList of ISO standards 22000–23999 (3,687 words) [view diff] exact match in snippet view article find links to article
Process capability statistics for characteristics following a multivariate normal distribution ISO 22514-7:2012 Part 7: Capability of measurement processes